173 research outputs found

    Boosting Method in Approximately Solving Linear Programming with Fast Online Algorithm

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    In this paper, we develop a new algorithm combining the idea of ``boosting'' with the first-order algorithm to approximately solve a class of (Integer) Linear programs(LPs) arisen in general resource allocation problems. Not only can this algorithm solve LPs directly, but also can be applied to accelerate the Column Generation method. As a direct solver, our algorithm achieves a provable O(n/K)O(\sqrt{n/K}) optimality gap, where nn is the number of variables and KK is the number of data duplication bearing the same intuition as the boosting algorithm. We use numerical experiments to demonstrate the effectiveness of our algorithm and several variants

    PyHGL: A Python-based Hardware Generation Language Framework

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    Hardware generation languages (HGLs) increase hardware design productivity by creating parameterized modules and test benches. Unfortunately, existing tools are not widely adopted due to several demerits, including limited support for asynchronous circuits and unknown states, lack of concise and efficient language features, and low integration of simulation and verification functions. This paper introduces PyHGL, an open-source Python framework that aims to provide a simple and unified environment for hardware generation, simulation, and verification. PyHGL language is a syntactical superset of Python, which greatly reduces the lines of code (LOC) and improves productivity by providing unique features such as dynamic typing, vectorized operations, and automatic port deduction. In addition, PyHGL integrates an event-driven simulator that simulates the asynchronous behaviors of digital circuits using three-state logic. We also propose an algorithm that eliminates the calculation and transmission overhead of unknown state propagation for binary stimuli. The results suggest that PyHGL code is up to 6.1x denser than traditional RTL and generates high-quality synthesizable RTL code. Moreover, the optimized simulator achieves 2.9x speed up and matches the performance of a commonly used open-source logic simulator

    Adaptive distance-based band hierarchy (ADBH) for effective hyperspectral band selection.

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    Band selection has become a significant issue for the efficiency of the hyperspectral image (HSI) processing. Although many unsupervised band selection (UBS) approaches have been developed in the last decades, a flexible and robust method is still lacking. The lack of proper understanding of the HSI data structure has resulted in the inconsistency in the outcome of UBS. Besides, most of the UBS methods are either relying on complicated measurements or rather noise sensitive, which hinder the efficiency of the determined band subset. In this article, an adaptive distance-based band hierarchy (ADBH) clustering framework is proposed for UBS in HSI, which can help to avoid the noisy bands while reflecting the hierarchical data structure of HSI. With a tree hierarchy-based framework, we can acquire any number of band subset. By introducing a novel adaptive distance into the hierarchy, the similarity between bands and band groups can be computed straightforward while reducing the effect of noisy bands. Experiments on four datasets acquired from two HSI systems have fully validated the superiority of the proposed framework

    Thermal barrier coatings on polymer materials

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    Polyimide matrix composite (PIMC) has been widely used to replace metallic parts due to its low density and high strength. It is considered as an effective approach to improve thermal oxidation resistance, operation temperature and lifetime of PIMC by depositing a protection coating. The objective of the research was to fabricate a series of thermal barrier coatings (TBCs) on PIMC by a combined sol-gel/sealing treatment process and air plasma spraying (APS). By optimizing the experimental parameters, thermal shock resistance, thermal oxidation resistance and thermal ablation resistance of PIMC could be improved significantly. The ZrO2 sol was prepared by sol-gel process and the effects of the different organic additions on phase structure, crystallite size and crystal growth behavior of the ZrO2 nanocrystallite were investigated. The addition of HAc and DMF were beneficial to decrease the crystallite size and alter the activation energy for crystal growth, further inducing the crystallization of ZrO2 nanocrystallite at low temperature (300ºC) and the stability of tetragonal ZrO2 at 600ºC. Based on the optimized parameters of the sol preparation, the ZrO2/phosphates duplex coating was fabricated on PIMC via a combined sol-gel and sealing treatment process. The sealing mechanism of the phosphates in the duplex coating was primarily attributed to the adhesive binding of the phosphates and the chemical bonding between the sealant and the coating. It was demonstrated that the duplex coating exhibited excellent thermal shock resistance and no apparent delamination or spallation occurred. Relatively, the duplex coating with the thickness of 150 μm provided excellent thermal oxidation and thermal ablation resistance for the polymer substrate. However, the presence of cracks and delamination in the coatings provided the channels for oxygen diffusion, causing the final failure of the protection coating. Figure 4 – TBCs on CFPI The Zn/YSZ and Al/YSZ coating systems were successfully deposited on PIMC by APS. Metals with comparatively low melting point as the bond coats (Cu, Al, Zn) were beneficial to increase thermal shock resistance of the coating systems. In comparison with the Al/YSZ coating system, the Zn/YSZ coating exhibited the better thermal shock resistance, which was ascribable to the lower residual stress in the Zn layer after deposition and the lower thermal stress induced during thermal shock test. For these coatings, the increase in surface toughness of the substrate as well as the decrease in thickness of metal layer favored the improvement of thermal shock resistance of the coatings. With the temperature increases, thermal shock lifetime of the coatings decreased disastrously. However, the difference was that the slight increase of the thickness of YSZ layer favored the increase in thermal shock resistance of the Al/YSZ coatings, while for the Zn/YSZ coating systems the increase in the thickness of YSZ layer made thermal shock resistance weaken. Owing to the protection of Zn/YSZ and Al/YSZ coating systems, the time for 5 wt% weight loss of the sample was prolonged from 16 h to 50 h when oxidation at 400ºC; as the oxidation temperature increased to 450ºC, the time for 5wt% weight loss was extended from 5 h to 13 h. By depositing different coatings, the anti-ablation property of PIMC was significantly improved. During property testing, the formation of cracks and delamination in the coating and the occurrence of the spallation led to the failure of the coating systems, which was mainly due to the residual stress during the deposition process, thermal stress induced by the mismatch in thermal expansion coefficient and further oxidation of the substrate. Please click Additional Files below to see the full abstract

    Tree ring δ18O reveals no long-term change of atmospheric water demand since 1800 in the northern Great Hinggan Mountains, China

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    Global warming will significantly increase transpirational water demand, which could dramatically affect plant physiology and carbon and water budgets. Tree ring δ18O is a potential index of the leaf-to-air vapor-pressure deficit (VPD) and therefore has great potential for long-term climatic reconstruction. Here we developed δ18O chronologies of two dominant native trees, Dahurian larch (Larix gmelinii Rupr.) and Mongolian pine (Pinus sylvestris var. mongolica), from a permafrost region in the Great Hinggan Mountains of northeastern China. We found that the July–August VPD and relative humidity were the dominant factors that controlled tree ring δ18O in the study region, indicating strong regulation of stomatal conductance. Based on the larch and pine tree ring δ18O chronologies, we developed a reliable summer (July–August) VPD reconstruction since 1800. Warming growing season temperatures increase transpiration and enrich cellulose 18O, but precipitation seemed to be the most important influence on VPD changes in this cold region. Periods with stronger transpirational demand occurred around the 1850s, from 1914 to 1925, and from 2005 to 2010. However, we found no overall long-term increasing or decreasing trends for VPD since 1800, suggesting that despite the increasing temperatures and thawing permafrost throughout the region, forest transpirational demand has not increased significantly during the past two centuries. Under current climatic conditions, VPD did not limit growth of larch and pine, even during extremely drought years. Our findings will support more realistic evaluations and reliable predictions of the potential influences of ongoing climatic change on carbon and water cycles and on forest dynamics in permafrost regions

    Fractalkine/CX3CR1 Contributes to Endometriosis-Induced Neuropathic Pain and Mechanical Hypersensitivity in Rats

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    Pain is the most severe and common symptom of endometriosis. Its underlying pathogenetic mechanism is poorly understood. Nerve sensitization is a particular research challenge, due to the limitations of general endometriosis models and sampling nerve tissue from patients. The chemokine fractalkine (FKN) has been demonstrated to play a key role in various forms of neuropathic pain, while its role in endometriotic pain is unknown. Our study was designed to explore the function of FKN in the development and maintenance of peripheral hyperalgesia and central sensitization in endometriosis using a novel endometriosis animal model developed in our laboratory. After modeling, behavioral tests were carried out and the optimal time for molecular changes was obtained. We extracted ectopic tissues and L4–6 spinal cords to detect peripheral and central roles for FKN, respectively. To assess morphologic characteristics of endometriosis-like lesions—as well as expression and location of FKN/CX3CR1—we performed H&E staining, immunostaining, and western blotting analyses. Furthermore, inhibition of FKN expression in the spinal cord was achieved by intrathecal administration of an FKN-neutralizing antibody to demonstrate its function. Our results showed that implanted autologous uterine tissue around the sciatic nerve induced endometriosis-like lesions and produced mechanical hyperalgesia and allodynia. FKN was highly expressed on macrophages, whereas its receptor CX3CR1 was overexpressed in the myelin sheath of sciatic nerve fibers. Overexpressed FKN was also observed in neurons. CX3CR1/pp38-MAPK was upregulated in activated microglia in the spinal dorsal horn. Intrathecal administration of FKN-neutralizing antibody not only reversed the established mechanical hyperalgesia and allodynia, but also inhibited the expression of CX3CR1/pp38-MAPK in activated microglia, which was essential for the persistence of central sensitization. We concluded that the FKN/CX3CR1 signaling pathway might be one of the mechanisms of peripheral hyperalgesia in endometriosis, which requires further studies. Spinal FKN is important for the development and maintenance of central sensitization in endometriosis, and it may further serve as a novel therapeutic target to relieve persistent pain associated with endometriosis

    Protecting privacy in microgrids using federated learning and deep reinforcement learning

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    This paper aims to improve the energy management efficiency of home microgrids while preserving privacy. The proposed microgrid model includes energy storage systems, PV panels, loads, and the connection to the main grid. A federated multi-objective deep reinforcement learning architecture with Pareto fronts is proposed for total carbon emission and electricity bills optimization. The privacy of data is protected by federated learning, by which the original data will not be uploaded to the server. Numerical results show that compared with the traditional single Deep-Q network, using the proposed method the accumulated carbon emission decreased by 3 and the electricity bills decreased by 21
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